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Nº de artículo:
181476783
Hailo-8 M.2 AI Accelerator Module 26TOPS Hailo8 Support Linux/Windows
Nº de artículo:
181476783
CLP 287869
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Unlock unprecedented AI performance for your edge devices with the Hailo-8 M.2 module, delivering 26 TOPS and 2.5W power consumption.
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What Stands Out
High Performance
Delivering an impressive 26 TOPS, the Hailo-8 M.2 AI accelerator module significantly enhances AI processing, providing power users with exceptional speed and efficiency for demanding applications.
Raspberry Pi Compatibility
Seamlessly integrates with Raspberry Pi 5, empowering users to upgrade their projects with advanced AI capabilities, making it an ideal choice for hobbyists and developers.
Multi-OS Support
Compatible with both Linux and Windows systems, this versatile accelerator module allows flexibility in development environments, catering to a diverse range of user preferences and project requirements.
Detalles de producto
| CPU Model | Others |
| Connectivity Technology | PCIe Gen3, 4-lane |
| Operating System | Linux, Windows 10 |
| Processor Brand | Hailo |
| Compatible Devices | Raspberry Pi 5 |
| RAM Memory Technology | LPDDR4 |
| Processor Count | 1 |
| Brand | Unistorm |
| Model Name | Hailo-8 M.2 AI Accelerator Module |
| Built-In Media | User Manual |
| UPC | 797465078001 |
| Manufacturer | UNISTORM |
| Model Number | Hailo-8 |
| Mfr Part Number | Hailo-8 |
| Included Components | User Manual |
| Item Weight | 0.15 lbs (70 grams) |
Who Should Buy?
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AI Enthusiasts
Users interested in developing AI applications can leverage the Hailo-8's powerful processing capabilities for innovative projects.
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Developers
Software developers can utilize this module for prototyping and testing machine learning models using Raspberry Pi 5 environments.
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Educational Institutions
Schools and universities can use this accelerator for teaching AI and machine learning concepts in hands-on projects.
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Casual Users
Individuals who are not tech-savvy may find it challenging to set up and utilize this advanced AI module effectively.
DESCRIPCIÓN DEL PRODUCTO
Hailo-8 M.2 AI Accelerator Module 26TOPS Hailo8 Support Linux/Windows
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Preguntas y respuestas de los clientes
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Pregunta:
What is the power consumption of the Hailo-8 M.2 module?
Respuesta: The typical power consumption is 2.5W, with a maximum of 8.65W. -
Pregunta:
Which AI frameworks are supported by this module?
Respuesta: It supports TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch frameworks. -
Pregunta:
What temperature range can the Hailo-8 module operate in?
Respuesta: It can operate in a temperature range of -40°C to 85°C.
Unistorm Acceleration Sensors Hailo-8 Editorial Review
Hailo-8 M.2 AI Accelerator Module 26TOPS Hailo8 Support Linux/Windows is an impressive piece of hardware offering significant processing power for AI applications, particularly in image analysis and inference tasks. Many users have reported successful integration with their setups, including those using Proxmox and Debian, although there are challenges with manual device ID configuration. The device excels at offloading inference tasks from the CPU, allowing other applications to run more smoothly. However, it’s worth noting that some users have raised concerns about its performance, suggesting that under certain conditions, it may not reach its full potential of 26TOPS, as indicated by issues in comparison to other manufacturers. Additionally, while the product is flexible, it is not suited for LLMs.
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ventajas
- Significant processing power for AI applications
- Integrates well with Proxmox and Debian
- Great for image analysis and inference tasks
- Lightweight at only 0.2 lbs
- Compatible with Raspberry Pi 5
Contras
- Integration requires manual device ID adjustment in some setups
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CLP 287869
Haz tu pedido ahora y recíbelo por ahí Sábado, Agosto 29
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características y beneficios
- Delivers 26 Tera-Operations Per Second (TOPS) for unmatched AI performance.
- Consumes just 2.5W of typical power, ensuring high efficiency.
- Supports multi-stream and multi-model processing for real-time AI inferencing.
- Compatible with major AI frameworks like TensorFlow, Pytorch, and Keras.
- Designed for extreme conditions, operating in -40°C to 85°C temperature range.
- Easy integration with existing devices through PCIe Gen3 interface.
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